Are GPUs Really Expensive? Benchmarking GPUs for Inference on Databricks Clusters
It is no secret that GPUs are critical for artificial intelligence and deep learning applications since their highly-efficient architectures make them ideal for...
Moneyball 2.0: Real-time Decision Making With MLB’s Statcast Data
The Oakland Athletics baseball team in 2002 used data analysis and quantitative modeling to identify undervalued players and create a competitive lineup on...
GPU-accelerated Sentiment Analysis Using Pytorch and Huggingface on Databricks
Sentiment analysis is commonly used to analyze the sentiment present within a body of text, which could range from a review, an email...
Introducing Apache Spark™ 3.2
We are excited to announce the availability of Apache Spark™ 3.2 on Databricks as part of Databricks Runtime 10.0 . We want to...
MLflow for Bayesian Experiment Tracking
This post is the third in a series on Bayesian inference ( [1] , [2] ). Here we will illustrate how to use...
Pandas API on Upcoming Apache Spark™ 3.2
We're thrilled to announce that the pandas API will be part of the upcoming Apache Spark™ 3.2 release. pandas is a powerful, flexible...
Catalog and Discover Your Databricks Notebooks Faster
This is a collaborative post from Databricks and Elsevier. We thank Darin McBeath, Director Disruptive Technologies -- Elsevier, for his contributions. As a...
Managing Model Ensembles With MLflow
In machine learning, an ensemble is a collection of diverse models that provide more predictive power together than any single model would on...
Real-time Point-of-Sale Analytics With a Data Lakehouse
Disruptions in the supply chain – from reduced product supply and diminished warehouse capacity – coupled with rapidly shifting consumer expectations for seamless...
Announcing Databricks Autologging for Automated ML Experiment Tracking
Machine learning teams require the ability to reproduce and explain their results--whether for regulatory, debugging or other purposes. This means every production model...